Comparative Performance Analysis of Slime Mould Algorithm For Efficient Design of Proportional–Integral–Derivative Controller

This paper deals with the performance analysis of a recently proposed metaheuristic algorithm known as the slime mould algorithm (SMA). This algorithm has been proved to be effective on several benchmark functions and constraint problems. This study further demonstrates its ability based on optimizing real-life engineering problems. Thus, the optimization ability of the SMA has been assessed by adopting proportional-integral-derivative (PID) controllers to regulate the speed of a direct current (DC) motor and maintaining the terminal output of an automatic voltage regulator (AVR) system. The obtained results were compared with the controller performances designed by other competitive metaheuristic algorithms, such as Harris hawks optimization (HHO), atom search optimization (ASO), and grey wolf optimization (GWO) algorithms for DC motor and symbiotic organisms search (SOS), local unimodal sampling (LUS), and many optimizing liaisons (MOL) algorithms for AVR system. The results showed that the PID controllers tuned by the SMA technique have superior performance compared to other counterparts.

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